
# generate table F2

# load packages
library(rio) # load data
library(tidyverse) # data manipulation
library(stargazer) # generate tables
library(brglm2) # estimate penalized logit
library(lmtest) # cluster standard errors
library(sandwich) # cluster standard errors

# set working directory
setwd("~/replication_files/")

# load data for analysis
data_with_dictionary <- import("data/full_data.csv") %>%
  mutate(across(c(imf_program,field_discovery,grad_school_econ_usa,iso3c,year), as.factor)) # treat factors as factors

# model 1, table F2
ols1 <- lm(policy_passage ~ resource_mentions_tfidf_lag + 
             previous_policy +  grad_school_econ_usa + fdi_performance_index_lag +
             imf_program + price_crudeoil_lag + price_crudeoil_difference + 
             resource_rents_lag + log_gdp_per_capita_lag + gdp_growth_lag + field_discovery_lag + 
             polyarchy + left_executive + protest + year + iso3c, data = data_with_dictionary)

# cluster standard errors
ols1_r <- ols1 %>% 
  coeftest(vcovHC(ols1, type = 'HC0', cluster =  ~ iso3c))

# model 2, table F2
logit1 <- glm(policy_passage ~ resource_mentions_tfidf_lag + 
                previous_policy +  grad_school_econ_usa + fdi_performance_index_lag +
                imf_program + price_crudeoil_lag + price_crudeoil_difference + 
                resource_rents_lag + log_gdp_per_capita_lag + gdp_growth_lag + field_discovery_lag + 
                polyarchy + left_executive + protest + year + iso3c, 
              data = data_with_dictionary, family = binomial(link="logit"), method = "brglmFit",
              slowit = 0.8, maxit = 500)

# cluster standard errors
logit1_r <- logit1 %>% 
  coeftest(vcovHC(logit1, type = 'HC0', cluster =  ~ iso3c))

# generate table F2
stargazer(ols1_r,logit1_r, # type = "text",
          omit = c("iso3c","year"), 
          dep.var.labels = "Policy Passage",
          covariate.labels = c("Natural Resource Term Frequency (TF-IDF), t--1", "Previous Policy Passage = 1",
                               "Technocratic Finance Minister = 1", "FDI Performance Index",
                               "IMF Program = 1", "Crude Oil Price, t--1", "Crude Oil Price, Delta",
                               "Resource Rents, t--1", "Log GDP Per Capita, t--1", "GDP Growth, t--1", "Field Discovery = 1, t--1",
                               "Polyarchy", "Left Executive", "Protest Count"),
          keep.stat = c("n", "rsq", "f", "ll", "aic"))

# retrieve fit stats
stargazer(ols1,logit1, # type = "text",
          omit = c("iso3c","year"), 
          dep.var.labels = "Policy Passage",
          covariate.labels = c("Natural Resource Term Frequency (TF-IDF), t--1", "Previous Policy Passage = 1",
                               "Technocratic Finance Minister = 1", "FDI Performance Index",
                               "IMF Program = 1", "Crude Oil Price, t--1", "Crude Oil Price, Delta",
                               "Resource Rents, t--1", "Log GDP Per Capita, t--1", "GDP Growth, t--1", "Field Discovery = 1, t--1",
                               "Polyarchy", "Left Executive", "Protest Count"),
          keep.stat = c("n", "rsq", "f", "ll", "aic"))

